Machine Learning Engineer II (Servicing ML)

Latitude; Las Vegas, Northern (NV, KY); Hybrid; USD 146,000 - 206,000; Full time

Benefits offered by this job

100% subsidized medical coverage for你u

Job summary

Affirm is seeking a machine learning engineer to build AI systems that automate dispute, chargeback handling, and refunds, with structured outputs from unstructured data. You will prototype models, run offline experiments, and deploy best approaches to production with risk controls.

You will collaborate across Engineering, Servicing Operations, Product, and ML Platform to define requirements and communicate results clearly to both technical and non-technical audiences.

Qualifications

• 2+ years of experience as a machine learning engineer.
• Strong Python skills and production-quality code.
• Experience building and evaluating models for tabular classification (LightGBM/XGBoost/CatBoost).
• Experience with LLM APIs (OpenAI, Anthropic) including structured extraction and prompt engineering.
• Familiarity with document/unstructured data processing (PDF/image extraction).
• Experience with ML lifecycle tooling (Kubeflow, Airflow, MLflow).
• Proficient with AI-powered developer tools (Claude Code, Cursor).
• Ability to write clear, well-tested, extensible code and navigate large codebases.
• Strong communication and collaboration skills.
• Bachelor's degree or equivalent practical experience.

Responsibilities

• Develop AI systems that automate dispute and chargeback handling with structured outputs.
• Build models to automate refunds and speed up customer recoveries.
• Create and maintain evidence extraction pipelines using LLM-powered workflows.
• Prototype new modeling ideas, run offline experiments, and push best approaches to production with risk controls.
• Collaborate with Engineering, Servicing Operations, Product, and ML Platform to define requirements and communicate results.

Skills

Python

Production code

Tabular models

LightGBM/XGBoost/CatBoost

LLM APIs

LangChain/ LangGraph

Unstructured data processing

ML lifecycle tooling

AI developer tools

Code reviews

Communication

Bachelor's degree or equivalent

Education

Bachelor's degree or equivalent

Tools

LightGBM

XGBoost

CatBoost

LangChain

LangGraph

Kubeflow

Airflow

MLflow

Job description

Affirm is reinventing credit to make it more honest and friendly, giving consumers the flexibility to buy now and pay later without any hidden fees or compounding interest.

On the Servicing ML team, you will build and improve machine learning and AI systems that automate customer operations such as disputes, returns, fraud, and chargebacks to make the best decisions for affirm and our customers. You will work closely with experienced ML engineers, platform partners, and cross‑functional stakeholders to take models from idea to prototype to production, and to keep them healthy with strong measurement and monitoring.

What You’ll Do

• You will develop AI systems that automate dispute and chargeback handling using structured evidence and business logic, creating a better experience for our customers.
• You will build models that automate refunds, getting money back to our customers faster.
• You will build and maintain evidence extraction pipelines that process unstructured data using LLM-powered workflows to produce structured, actionable outputs.
• You will prototype new modeling ideas, run offline experiments, and drive the best-performing approaches into production with appropriate risk controls.
• You will collaborate across Engineering, Servicing Operations, Product, and ML Platform to define requirements, evaluate tradeoffs, and communicate results clearly to both technical and non‑technical audiences.

What We Look For

• You have a total of 2+ years of experience as a machine learning engineer
• Strong Python skills and experience writing production-quality code
• Experience building and evaluating models for tabular classification problems (preferably gradient-boosted decision trees like LightGBM/XGBoost/CatBoost).
• Experience building applications with LLM APIs (e.g., OpenAI, Anthropic), including structured extraction, prompt engineering, and orchestration frameworks like LangChain or LangGraph.
• Familiarity with document and unstructured data processing (PDF/image extraction, text parsing, or similar).
• Experience with ML lifecycle tooling for training orchestration, experimentation, and model monitoring (e.g., Kubeflow, Airflow, MLflow, or equivalent internal platforms).
• Proficient in using AI-powered developer tools (e.g., Claude Code, Cursor, or similar) to accelerate iteration, debugging, and code quality as part of day‑to‑day development workflows.
• You have mastered taking a simple problem or business scenario into a solution that interacts with multiple software components, and executing on it by writing clear, easily understood, well‑tested and extensible code.
• You are comfortable navigating a large code base, debugging others' code, and providing feedback to other engineers through code reviews.
• Your experience demonstrates that you take ownership of your growth, proactively seeking feedback from your team, your manager, and your stakeholders.
• You have strong verbal and written communication skills that support effective collaboration with our global engineering team.
• This position requires either equivalent practical experience or a Bachelor’s degree in a related field

Base Pay Grade

- L

Equity Grade

- 6

Employees new to affirm typically come in at the start of the pay range. affirm focuses on providing a simple and transparent pay structure which is based on a variety of factors, including location, experience and job‑related skills.

Base pay is part of a total compensation package that may include equity rewards, monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents.)

USA base pay range (CA, WA, NY, NJ, CT) per year: $165,000 - $225,000

USA base pay range (all other U.S. states) per year: $146,000 - $206,000

Affirm is proud to be a remote‑first company! The majority of our roles are remote and you can work almost anywhere within the country of employment. affirmers in proximal roles have the flexibility to work remote, but will occasionally be required to work out of their assigned affirm office. A limited number of roles remain office‑based due to the nature of their job responsibilities.

Benefits

We're extremely proud to offer competitive benefits that are anchored to our core value of people come first. Some key highlights of our benefits package include:

• Health care coverage - affirm covers all premiums for all levels of coverage for you and your dependents
• Flexible Spending Wallets - generous stipends for spending on Technology, Food, various Lifestyle needs, and family forming expenses
• Time off - competitive vacation and holiday schedules allowing you to take time off to rest and recharge
• ESPP - An employee stock purchase plan enabling you to buy shares of affirm at a discount

We believe It's On Us to provide an inclusive interview experience for all, including people with disabilities. We are happy to provide reasonable accommodations to candidates in need of individualized support during the hiring process.

[For U.S. positions that could be performed in Los Angeles or San Francisco] Pursuant to the San Francisco Fair Chance Ordinance and Los Angeles Fair Chance Initiative for Hiring Ordinance, affirm will consider for employment qualified applicants with arrest and conviction records.